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--- |
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language: |
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- vi |
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license: mit |
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base_model: FacebookAI/xlm-roberta-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: xlm-roberta-large_baseline_words |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# xlm-roberta-large_baseline_words |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the covid19_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0850 |
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- Patient Id: 0.9840 |
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- Name: 0.7711 |
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- Gender: 0.9767 |
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- Age: 0.9821 |
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- Job: 0.8062 |
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- Location: 0.9570 |
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- Organization: 0.8784 |
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- Date: 0.9869 |
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- Symptom And Disease: 0.8688 |
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- Transportation: 1.0 |
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- F1 Macro: 0.9211 |
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- F1 Micro: 0.9459 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Patient Id | Name | Gender | Age | Job | Location | Organization | Date | Symptom And Disease | Transportation | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:| |
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| 0.2002 | 1.0 | 629 | 0.1212 | 0.9160 | 0.8349 | 0.8346 | 0.8122 | 0.5385 | 0.8769 | 0.7201 | 0.9553 | 0.7769 | 0.8587 | 0.8124 | 0.8586 | |
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| 0.0557 | 2.0 | 1258 | 0.1025 | 0.9594 | 0.8836 | 0.9533 | 0.9731 | 0.2841 | 0.9228 | 0.8301 | 0.9842 | 0.8545 | 0.9444 | 0.8590 | 0.9191 | |
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| 0.038 | 3.0 | 1887 | 0.0804 | 0.9741 | 0.7154 | 0.9732 | 0.9821 | 0.7615 | 0.9372 | 0.8576 | 0.9869 | 0.8461 | 0.9943 | 0.9028 | 0.9309 | |
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| 0.0222 | 4.0 | 2516 | 0.0862 | 0.9871 | 0.5567 | 0.9691 | 0.9862 | 0.8207 | 0.9553 | 0.8707 | 0.9847 | 0.8740 | 1.0 | 0.9005 | 0.9398 | |
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| 0.0148 | 5.0 | 3145 | 0.0850 | 0.9840 | 0.7711 | 0.9767 | 0.9821 | 0.8062 | 0.9570 | 0.8784 | 0.9869 | 0.8688 | 1.0 | 0.9211 | 0.9459 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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